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  "headline": "Gradient Descent and Optimization",
  "description": "Gradient descent is the fundamental optimization algorithm for training machine learning models. It iteratively adjusts parameters in the direction of steepest descent of the loss function. Variants: Batch GD (full dataset), Stochastic GD (single example), Mini-batch GD (small batches — standard).",
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      "name": "Adam: A Method for Stochastic Optimization",
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